Journal of UNG

Pulling information out of a genome has proved to be a challenging task, which requires complex statistical tools and powerful computers to run the analysis. And if results are to be delivered in a reasonable timeframe, you’d better ask for fast computers as well.

This sort of computing power is not available to all researchers interested in how animals inherit their physical traits. To counter this problem, Dr Sara Knott from the University of Edinburgh and her team developed GridQTL, a grid-based platform that provides fast and robust analysis to identify trait-related genome regions. These are called quantitative trait loci (QTL). Knott explains: “QTL are regions of the genome that have an effect on a given physical trait.” A knowledge of the QTL involved in the expression of a trait is crucial for our understanding of variation between individuals and how traits are passed on from generation to generation, she adds.

Respiratory infections are the main reason why children under five end up in hospital. However, in up to 40% of the cases it’s not possible to define the exact cause of the disease and this means that there are viruses still unknown to science.

Identifying as many viruses as possible improves the chances of correct diagnostics and helps to determine the best treatment for patients. Knowing which virus is responsible for which disease is also very important to detect potential epidemics or to assess the seriousness of viral infections.